Charging and discharging control method of energy storage system and energy storage system

Abstract

The application relates to a charge-discharge control method of an energy storage system and the energy storage system. The method comprises the following steps: collecting state information of at least one battery cluster in a battery stack; determining a current charge-discharge working condition of the battery stack, and when it is identified that at least one battery cluster is at the end of charge-discharge in the current charge-discharge working condition, predicting, according to the state information of the at least one battery cluster, a first time length for the at least one battery cluster to reach a charge-discharge cut-off boundary from a current state of charge through charge-discharge; adjusting a virtual state of charge of the at least one battery cluster according to the first time length and the state information corresponding to the at least one battery cluster; and coordinating the charge-discharge depth of the at least one battery cluster at the end of charge-discharge through the virtual state of charge. The method realizes the coordination and balance of the charge-discharge depth of each battery cluster at the end of charge-discharge, improves the overall energy utilization rate of the battery stack, and prolongs the service life of the battery stack.

Description

Technical Field

[0001] This application relates to the field of energy storage battery management technology, and in particular to a charging and discharging control method and an energy storage system. Background Technology

[0002] Energy storage systems consist of battery stacks, which are composed of multiple battery clusters connected in parallel. Due to factors such as cell dispersion, inter-cluster temperature differences, capacity differences, internal resistance differences, errors in state of charge (SOC) estimation, and differences in operating history, the state of charge of each battery cluster gradually becomes dispersed during charging and discharging. When the system is at the end of charging, battery clusters with higher SOC tend to approach the upper cutoff threshold first; when the system is at the end of discharging, battery clusters with lower SOC tend to approach the lower cutoff threshold first.

[0003] In traditional technology, if a single cluster in the battery stack reaches the charge / discharge cutoff boundary first, it will cause the entire battery stack to stop charging and discharging prematurely, resulting in a compression of the battery stack's charge / discharge depth. Summary of the Invention

[0004] Therefore, it is necessary to provide a charging and discharging control method and energy storage system that can avoid compressing the charging and discharging depth of the battery stack, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a charging and discharging control method for an energy storage system, comprising:

[0006] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0007] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0008] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0009] In one embodiment, the state information includes the current cluster voltage, current charge / discharge current, current state of charge, and current health state of at least one battery cluster; based on the state information of at least one battery cluster, predicting a first time interval from the current state of charge for at least one battery cluster to reach the charge / discharge cutoff boundary includes:

[0010] Based on the battery model and the current cluster voltage of at least one battery cluster, the confidence level of at least one battery cluster is obtained;

[0011] Based on the credibility of at least one battery cluster and the state information of at least one battery cluster, at least one target battery cluster participating in charge and discharge control is determined from the battery stack;

[0012] The first duration of the target battery cluster is determined based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

[0013] In one embodiment, the confidence level of at least one battery cluster is obtained based on the battery model and the current cluster voltage of at least one battery cluster, including:

[0014] Based on the battery model, the predicted cluster voltage of at least one battery cluster at the current moment is predicted;

[0015] The confidence level of at least one battery cluster is calculated based on the difference between the predicted cluster voltage and the current cluster voltage at the current moment.

[0016] In one embodiment, a first duration for the target battery cluster is determined based on the charge / discharge current, current state of charge, and health state of the target battery cluster involved in charge / discharge control, including:

[0017] Determine the current equivalent available capacity of the target battery cluster based on its current health status;

[0018] Determine the current remaining charge / discharge capacity of the target battery cluster based on its current equivalent available capacity and current state of charge.

[0019] The first duration of the target battery cluster is determined based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0020] In one embodiment, the status information further includes the current cluster temperature of at least one battery cluster; adjusting the virtual state of charge of at least one battery cluster according to the first duration and status information corresponding to the at least one battery cluster includes:

[0021] Based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time;

[0022] Based on the second duration, and the first duration of the target battery cluster involved in charge and discharge control, the current cluster temperature, the current health status, and the current state of charge, the coordination parameters of the target battery cluster are determined.

[0023] The virtual state of charge of the target battery cluster is adjusted based on the coordination parameters of the target battery cluster.

[0024] In one embodiment, adjusting the virtual state of charge of the target battery cluster according to the coordination parameters of the target battery cluster includes:

[0025] Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, the current virtual state of charge of the target battery cluster is updated to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0026] In one embodiment, coordination parameters for the target battery cluster are determined based on a second duration, a first duration of the target battery cluster involved in charge / discharge control, the current cluster temperature, the current health state, and the current state of charge, including:

[0027] Based on the state information of the target battery cluster, determine the degradation cost parameters of the target battery cluster;

[0028] Based on the attenuation cost parameters of the target battery cluster and the first and second durations, the coordination parameters of the target battery cluster are obtained.

[0029] In one embodiment, the degradation cost parameter of the target battery cluster is determined based on the state information of the target battery cluster, including:

[0030] Based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster;

[0031] The attenuation cost parameters of the target battery cluster are obtained based on multiple attenuation sub-components of the target battery cluster.

[0032] In one embodiment, after determining the current charge / discharge condition of the battery stack, the method further includes:

[0033] When the current charge / discharge condition of the battery stack is the charging condition, and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold, the battery cluster is determined to be at the end of the charging phase of the current charge / discharge condition.

[0034] When the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharge threshold, the battery cluster is determined to be at the end of the discharge of the current charge / discharge condition.

[0035] Secondly, this application also provides an energy storage system that performs the steps of the method as described in the first aspect. The energy storage system includes:

[0036] The acquisition module is used to acquire the status information of at least one battery cluster in the battery stack during charging and discharging.

[0037] The determination module is used to determine the current charging and discharging condition of the battery stack, and when it is identified that at least one battery cluster is at the end of the current charging and discharging condition, it predicts the first time from the current state of charge of at least one battery cluster to the charging and discharging cutoff boundary based on the state information of at least one battery cluster.

[0038] An adjustment module is used to adjust the virtual state of charge of at least one battery cluster based on the first duration and state information corresponding to at least one battery cluster; the virtual state of charge coordinates the charge and discharge depth of at least one battery cluster at the end of the charge and discharge process.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0041] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0042] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0044] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0045] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0046] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0047] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0048] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0049] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0050] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0051] The aforementioned energy storage system's charge / discharge control method and system collect state information of at least one battery cluster in the battery stack; determine the current charge / discharge condition of the battery stack; and when at least one battery cluster is identified as being at the end of the current charge / discharge condition, based on the state information of at least one battery cluster, predict the first time it will take for the at least one battery cluster to reach the charge / discharge cutoff boundary from its current state of charge; adjust the virtual state of charge of at least one battery cluster based on the first time and state information corresponding to the at least one battery cluster; and coordinate the charge / discharge depth of at least one battery cluster at the end of the charge / discharge process using the virtual state of charge. By predicting the first time each battery cluster will reach the charge / discharge cutoff boundary and dynamically adjusting the virtual state of charge of each battery cluster based on each first time, the coordinated balance of the charge / discharge depth of each battery cluster at the end of the charge / discharge process is achieved. This avoids the compression of the charge / discharge depth of the battery stack and prevents some battery clusters from entering the cutoff protection prematurely, thus reducing the overall usable capacity of the stack. Consequently, the overall energy utilization rate of the battery stack is improved, and the lifespan of the battery stack is extended. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is an application environment diagram of the charging and discharging control method of an energy storage system in one embodiment;

[0054] Figure 2 This is a flowchart illustrating the charging and discharging control method of an energy storage system in one embodiment;

[0055] Figure 3 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0056] Figure 4 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0057] Figure 5 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0058] Figure 6 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0059] Figure 7 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0060] Figure 8 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0061] Figure 9 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0062] Figure 10 This is a flowchart illustrating the charging and discharging control method of an energy storage system in another embodiment;

[0063] Figure 11 This is a structural block diagram of an energy storage system in one embodiment;

[0064] Figure 12 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0066] The charging and discharging control method for energy storage systems provided in this application can be applied to, for example... Figure 1 The application environment is shown. The energy storage system 102 includes at least one battery stack, and the battery stack includes multiple battery clusters 104. A data storage system can store the data that the energy storage system 102 needs to process. The data storage system can be integrated into the energy storage system 102 or placed in the cloud or on another network server. When the battery stack is charging and discharging, the energy storage system 102 collects the state information of at least one battery cluster 104 in the battery stack, and adjusts the virtual charge state of the battery cluster 104 based on the state information of the battery cluster 104.

[0067] In one embodiment, such as Figure 2As shown, a charging and discharging control method for an energy storage system is provided, which can be applied to... Figure 1 Taking the energy storage system in China as an example, this will be explained, including:

[0068] S201, Under the condition of charging and discharging of the battery stack, collect the status information of at least one battery cluster in the battery stack.

[0069] The status information of the battery cluster includes at least parameters such as the state of charge (SOC), voltage, current, and temperature of each battery cluster, which are used to characterize the current operating status and health of the battery cluster.

[0070] In this embodiment, the battery stack consists of multiple battery clusters connected in parallel or series, and each battery cluster includes several battery modules or cell units. Sensor data corresponding to each battery cluster can be read based on a preset acquisition period, and the data can be stored in the energy storage system's cache area according to timestamps.

[0071] For example, the battery stack may include multiple battery clusters connected in series or parallel, each battery cluster being equipped with a voltage sensor, a current sensor, and a temperature sensor. The energy storage system is connected to each sensor and periodically polls the voltage, current, and state of charge values ​​of each battery cluster when the battery stack is charging and discharging.

[0072] S202, when the current charging and discharging condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the current charging and discharging condition, the first time duration from the current state of charge of the at least one battery cluster to the charging and discharging cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0073] In this embodiment, the charging / discharging end is the stage where the state of charge of the battery cluster gradually approaches the upper limit of the charging cutoff during charging or the lower limit of the discharging cutoff during discharging. At this time, the charging / discharging rate of the battery cluster begins to change due to polarization voltage or thermal management constraints. For example, the upper limit of the charging cutoff can be the voltage rising to 4.2V or the state of charge rising to 100%, and the lower limit of the discharging cutoff can be the voltage dropping to 2.5V or the state of charge dropping to 0%.

[0074] Optionally, when the current charge / discharge condition of the battery stack is a charging condition, and the current state of charge (SOC) of at least one battery cluster is greater than or equal to the SOC charging threshold, the battery cluster is determined to be at the end of the charging phase of the current charge / discharge condition. For example, the current SOC of the battery cluster being greater than or equal to the SOC charging threshold can be expressed as: ,in, Battery cluster number A battery cluster, Number the control cycle, i.e., the first cycle. Each sampling or control moment, The state of charge (SOC) threshold is the threshold for entering the end-of-charge coordination zone.

[0075] Optionally, when the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge (SOC) of at least one battery cluster is less than or equal to the SOC discharge threshold, the battery cluster is determined to be at the end of the discharge phase of the current charge / discharge condition. The current SOC of the battery cluster being less than or equal to the SOC discharge threshold can be expressed as: ,in, The current state of charge, This is the state-of-charge (SOC) discharge threshold, i.e., the SOC threshold for entering the discharge end coordination region.

[0076] For example, the state of charge discharge threshold can be 20%. When the battery stack is in discharge condition and the current state of charge of at least one battery cluster is less than 20%, the battery cluster is identified as entering the discharge end. The voltage, current and temperature data of the battery cluster at the current moment are further obtained. Combined with the historical discharge curve of the battery cluster and the current discharge rate, the first time required for the battery cluster to discharge from the current state of charge to the cutoff lower limit can be predicted by the ampere-hour integration method or equivalent circuit model.

[0077] For example, the state of charge (SOC) charging threshold can be 80%. When the battery stack is in charging condition and the current SOC of at least one battery cluster is higher than 80%, the battery cluster is identified as entering the charging end. The voltage, current and temperature data of the battery cluster at the current moment are further obtained. Combined with the historical discharge curve and current discharge rate of the battery cluster, the first time required for the battery cluster to charge from the current SOC to the cutoff limit can be predicted by the ampere-hour integration method or equivalent circuit model.

[0078] S203, adjust the virtual state of charge of at least one battery cluster according to the first duration and state information corresponding to at least one battery cluster.

[0079] The virtual state of charge (VFC) is a logical variable maintained internally by the controller. The VFC coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0080] In the embodiments of this application, when there is a difference in the first duration of different battery clusters, it indicates that the time when each battery cluster reaches the charge / discharge cutoff boundary is different. By adjusting the virtual state of charge, the virtual state of charge of the battery cluster that reaches the cutoff boundary slower is brought closer to that of the battery cluster that reaches the cutoff boundary faster, and the virtual state of charge of the battery cluster that reaches the cutoff boundary faster is brought closer to that of the battery cluster that reaches the cutoff boundary slower, thereby balancing the actual charge / discharge depth of each battery cluster at the end of the charge / discharge process.

[0081] Optionally, under discharge conditions, after calculating the first duration of each battery cluster, the battery cluster with the shortest first duration is selected as the reference cluster. For other battery clusters besides the reference cluster, the virtual state of charge of the other battery clusters is reduced, so that the other battery clusters reach the cutoff lower limit earlier in the subsequent discharge process. Under charging conditions, the battery cluster with the shortest first duration is selected as the reference cluster. For other battery clusters besides the reference cluster, the virtual state of charge of the other battery clusters is increased, so that the other battery clusters reach the cutoff upper limit synchronously with the reference cluster at the end of charging.

[0082] Optionally, under discharge conditions, a reference duration can be determined based on the first duration of each battery cluster, and the virtual state of charge of each battery cluster can be adjusted according to the reference duration to make the time when each battery cluster reaches the lower discharge cutoff limit more consistent. Under charging conditions, a reference duration can be determined based on the first duration of each battery cluster, and the virtual state of charge of each battery cluster can be adjusted according to the reference duration to make the time when each battery cluster reaches the upper charging cutoff limit more consistent.

[0083] In the aforementioned energy storage system's charge / discharge control method, during the charging and discharging of the battery stack, the state information of at least one battery cluster in the stack is collected; the current charging / discharging condition of the battery stack is determined, and when at least one battery cluster is identified as being at the end of the current charging / discharging condition, the first time it takes for the at least one battery cluster to reach the charge / discharge cutoff boundary from its current state of charge is predicted based on the state information of the at least one battery cluster; the virtual state of charge of the at least one battery cluster is adjusted based on the first time and state information corresponding to the at least one battery cluster; the virtual state of charge coordinates the charge / discharge depth of the at least one battery cluster at the end of the charging / discharging process. By predicting the first time for each battery cluster to reach the charge / discharge cutoff boundary and dynamically adjusting the virtual state of charge of each battery cluster based on each first time, the coordinated balance of the charge / discharge depth of each battery cluster at the end of the charging / discharging process is achieved, preventing the charge / discharge depth of the battery stack from being compressed and avoiding the problem of some battery clusters entering the cutoff protection too early, which would lead to a decrease in the usable capacity of the entire stack. This improves the overall energy utilization rate of the battery stack and extends its service life.

[0084] In one embodiment, an implementation of S202 is provided, wherein the state information includes the current cluster voltage, current charge / discharge current, current state of charge, and current health state of at least one battery cluster, such as... Figure 3 As shown, the above-mentioned "predicting the first time duration for at least one battery cluster to reach the charge / discharge cutoff boundary from the current state of charge, based on the state information of at least one battery cluster" includes:

[0085] S301, based on the battery model and the current cluster voltage of at least one battery cluster, obtain the confidence level of at least one battery cluster.

[0086] In this embodiment, the battery model can be a pre-established mathematical model describing the relationship between battery cluster voltage and parameters such as state of charge, current, and temperature. The current cluster voltage is compared with the predicted value from the battery model to obtain the confidence level of at least one battery cluster.

[0087] For example, the battery model can be an equivalent circuit model or an electrochemical model. The current charge / discharge current, state of charge, and temperature are input into the battery model to obtain the predicted cluster voltage output by the battery model. The current cluster voltage is compared with the predicted cluster voltage to determine the difference between the current cluster voltage and the predicted cluster voltage. Then, based on the mapping relationship between the difference and the confidence level, the confidence level of the battery cluster is determined.

[0088] S302, based on the confidence level of at least one battery cluster and the state information of at least one battery cluster, determine at least one target battery cluster participating in charge-discharge control from the battery stack.

[0089] In this embodiment of the application, based on the credibility of each battery cluster and combined with parameters such as the current state of charge and health status in the status information, battery clusters with normal status and reliable data are selected as target battery clusters to participate in subsequent control, while battery clusters with low credibility or abnormal status are excluded, or the weight of the corresponding battery clusters participating in end-point coordination is reduced.

[0090] Optionally, for any battery cluster, if the confidence level of the battery cluster is lower than the confidence threshold, the battery cluster is marked as abnormal and not included in the target battery cluster range of the charge / discharge end control. Conversely, if the confidence level is higher than the confidence threshold, and the deviation between the current state of charge of the battery cluster and the average state of charge of the battery stack exceeds a preset range, or if the health status is lower than a preset value, the battery cluster can be excluded, and the remaining battery clusters can be identified as target battery clusters. For example, the confidence threshold can be 0.6, the preset range can be ±15%, and the preset value can be 80%.

[0091] The confidence threshold is a pre-set confidence reference value used to determine whether the measured data of the current cluster voltage of the battery cluster is reliable. The confidence threshold can be pre-set based on experimental data or pre-set based on the sensor acquisition accuracy.

[0092] For example, an initial set of target battery clusters can be determined first based on the credibility and credibility threshold of each battery cluster. This initial set of target battery clusters can be represented as follows: ,in, As a confidence threshold, Let represent the credibility of the i-th battery cluster. Further, based on the status information, the communication status, voltage consistency, and presence of temperature anomalies of each battery cluster can be determined. Battery clusters in the initial target battery cluster set that have good communication status, consistent cluster voltage, and temperatures within a preset temperature range are then identified as target battery clusters.

[0093] S303, determine the first duration of the target battery cluster based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

[0094] In this embodiment of the application, based on the current charge and discharge current of each target battery cluster, and combined with the state of charge and health state, the first time required for the target battery cluster to charge and discharge from the current state of charge to the cutoff boundary can be calculated by the ampere-hour integral method or by model prediction.

[0095] In the above-mentioned application embodiments, the reliability of each battery cluster is verified by the battery model, and the target battery clusters with valid data are selected to participate in the charge and discharge end control by combining the state information. Battery clusters with sensor abnormalities or state deviations are eliminated, thereby improving the accuracy of the first duration prediction and the reliability of the charge and discharge end control.

[0096] In one embodiment, one implementation of S301 above is provided, such as... Figure 4 As shown, the above-mentioned "obtaining the confidence level of at least one battery cluster based on the battery model and the current cluster voltage of at least one battery cluster" includes:

[0097] S401, based on the battery model, predicts the predicted cluster voltage of at least one battery cluster at the current moment.

[0098] In this embodiment of the application, the state information of each battery cluster collected at the current time is input into the battery model, and the predicted cluster voltage of each battery cluster at the current time is output after the battery model performs calculations.

[0099] For example, the battery model can employ an equivalent circuit model, which may include a voltage source describing the relationship between the battery's open-circuit voltage and state of charge, an RC network describing the battery's polarization effect, and a series resistor describing the ohmic internal resistance. By substituting the current state of charge, charging / discharging current, and temperature of each battery cluster into the battery model, the predicted cluster voltage of each battery cluster at the current moment can be obtained by solving the circuit equations.

[0100] S402, based on the difference between the predicted cluster voltage and the current cluster voltage of at least one battery cluster at the current moment, calculate the confidence level of at least one battery cluster.

[0101] In this embodiment, the predicted cluster voltage of each battery cluster at the current moment is calculated by subtracting the actual current cluster voltage collected by the battery cluster. The reliability of each battery cluster is then calculated based on the cluster voltage difference. The smaller the deviation between the predicted cluster voltage and the actual cluster voltage, the higher the degree of consistency between the actual operating characteristics of the battery cluster and the battery model, and the higher the reliability of its state information; conversely, the larger the deviation, the lower the reliability.

[0102] As an alternative implementation, for each battery cluster, the predicted cluster voltage is calculated. With current cluster voltage The absolute deviation ΔV between the two values ​​is used to determine the credibility of the battery cluster based on the mapping relationship between ΔV and credibility.

[0103] As another alternative implementation method, taking a first-order RC equivalent model as an example, the first... Each battery cluster at time The predicted cluster terminal voltage can be expressed as Equation 1:

[0104] (Equation 1)

[0105] in, This is an open-circuit voltage function, representing the mapping relationship between SOC and temperature to open-circuit voltage; To predict SOC, let represent the th The predicted SOC value of each battery cluster before the update; The temperature of the cluster represents the temperature of the first cluster. Current temperature of each battery cluster; Let be the cluster current, representing the th Current current of each battery cluster; For the equivalent ohmic internal resistance, let represent the first... Ohmic internal resistance parameters in a battery cluster model; To predict the polarization voltage, the first... The polarization voltage prediction value of each battery cluster was measured before the update.

[0106] Furthermore, determine the first The voltage difference between the measured voltage and the predicted voltage of a battery cluster The covariance of the voltage difference is defined as Equation 2:

[0107] (Equation 2)

[0108] in, The observation matrix or Jacobian matrix is ​​the observation function. For the state vector The matrix obtained by taking the partial derivative characterizes the sensitivity of the measurement value to changes in state; the observation function... To map the state vector to a function of observed quantities such as terminal voltage, For the first The state variable vector of each battery cluster, such as SOC and polarization voltage; Let be the predicted state covariance matrix, representing the th Uncertainty matrix of state estimation before measurement update for each battery cluster; To measure the noise covariance, let represent the th Individual battery cluster voltage measurement noise or observation noise intensity; Used to measure whether the amount of innovation is abnormal under current uncertainty.

[0109] Furthermore, based on the voltage difference and covariance, the normalized coresidual is defined as Equation 3:

[0110] (Equation 3)

[0111] Smoothing the normalized residuals yields the smoothed residuals as shown in Equation 4:

[0112] (Equation 4)

[0113] in, This is the smoothing coefficient. Further, The mapping to the credibility coefficient is shown in Equation 5:

[0114] (Equation 5)

[0115] in, The credibility coefficient is the first The reliability of the current SOC estimation results for each battery cluster; The mapping coefficient is the attenuation coefficient that maps the residual to the confidence level.

[0116] In the above-mentioned application embodiments, the cluster voltage is predicted by the battery model and the difference between the predicted and measured current cluster voltage is calculated to evaluate the reliability of each battery cluster. No additional hardware is required, and the computational efficiency is high.

[0117] In one embodiment, one implementation of S303 above is provided, such as... Figure 5 As shown, the aforementioned "determining the first duration of the target battery cluster based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control" includes:

[0118] S501, determine the current equivalent available capacity of the target battery cluster based on the current health status of the target battery cluster.

[0119] In this embodiment, the current equivalent available capacity of the target battery cluster is determined based on its current health status and rated capacity. Optionally, the current equivalent available capacity can be determined as the product of the current health status and rated capacity of the target battery cluster. For example, the current equivalent available capacity can be expressed as... ,in, For the first The rated capacity of each battery cluster For the first The current health status of each battery cluster. For the first The current equivalent available capacity of each battery cluster.

[0120] For example, if the rated capacity of any target battery cluster is 100Ah and the current health status is a capacity retention rate of 92%, then the current equivalent usable capacity is 100Ah × 92% = 92Ah. Optionally, the current health status can be determined based on the actual charge-discharge integration results to improve the accuracy of the equivalent usable capacity.

[0121] S502, determine the current remaining charge / discharge capacity of the target battery cluster based on the current equivalent available capacity and current state of charge of the target battery cluster.

[0122] In this embodiment of the application, the remaining charge and discharge capacity of the target battery cluster under the current operating conditions is calculated based on the current equivalent available capacity, the current state of charge, and the cutoff state of charge.

[0123] Optionally, the current equivalent available capacity and current state of charge of the target battery cluster can be substituted into a preset formula to obtain the current remaining charge and discharge capacity of the target battery cluster.

[0124] Optionally, the difference between the current state of charge and the cutoff state of charge of the target battery cluster can be determined first; then, based on the current equivalent available capacity of the target battery cluster and the difference between the current state of charge and the cutoff state of charge of the target battery cluster, the current remaining charge and discharge capacity of the target battery cluster can be determined.

[0125] For example, under charging conditions, the first The remaining rechargeable capacity of each battery cluster from the charging cutoff boundary is shown in Equation 6:

[0126] (Equation 6)

[0127] in, The remaining rechargeable capacity, i.e., the first... The remaining rechargeable capacity of each battery cluster from the charging cutoff boundary; For the first The current actual state of charge of each battery cluster is represented on a scale of 0 to 100. This is the charging cutoff SOC threshold, which is the SOC value corresponding to the charging cutoff boundary.

[0128] For example, under discharge conditions, the first The remaining rechargeable capacity of each battery cluster from the discharge cutoff boundary is shown in Equation 7:

[0129] (Equation 7)

[0130] in, The remaining capacity, i.e., the first... The remaining dischargeable capacity of each battery cluster from the discharge cutoff boundary; This is the discharge cutoff SOC threshold, which is the SOC value corresponding to the discharge cutoff boundary of the battery cluster.

[0131] S503, determine the first duration of the target battery cluster based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0132] In this embodiment of the application, the ratio of the current remaining charge / discharge capacity to the current charge / discharge current value is used as the remaining time required for the battery cluster to continue charging and discharging to reach the charge / discharge cutoff boundary under the current charge / discharge current, i.e., the first duration.

[0133] Optionally, during charging, the first duration can be as shown in Equation 8:

[0134] (Equation 8)

[0135] in, The first duration under charging conditions, i.e., the first... The estimated time for each battery cluster to reach the cutoff boundary under charging conditions; The charging current, i.e., the first The positive current used when charging a battery cluster; To prevent a zero denominator, i.e., to prevent the current from being too small to result in a positive number with a zero denominator, we can further combine equations 6 and 8 to obtain equation 9:

[0136] (Equation 9)

[0137] Optionally, under discharge conditions, the first duration can be as shown in Equation 10:

[0138] (Equation 10)

[0139] in, The first duration under discharge conditions, i.e., the first... The estimated time for each battery cluster to reach the cutoff boundary under discharge conditions; The discharge current, i.e., the first The absolute value of the current when a battery cluster discharges; To prevent a small, zero-valued fraction, i.e., to prevent the current from being too small to result in a positive number with a zero denominator, we can further combine equations 7 and 10 to obtain equation 11:

[0140] (Equation 11)

[0141] For example, if the current remaining discharge capacity of a target battery cluster under discharge conditions is 46Ah and the current discharge current is 46A, then the first duration is 46Ah / 46A=1h.

[0142] In the above-mentioned application embodiments, the equivalent available capacity is determined by the current health status of the battery cluster, and the first duration is calculated by combining the current state of charge and the charging and discharging current. This fully considers the impact of battery aging on capacity and remaining operating time, making the prediction result of the first duration more consistent with the actual state of the battery and improving the accuracy of the charging and discharging end control.

[0143] In one embodiment, an implementation of S203 is provided, wherein the status information further includes the current cluster temperature of at least one battery cluster; such as Figure 6 As shown, the above-mentioned "adjusting the virtual state of charge of at least one battery cluster according to the first duration and state information corresponding to at least one battery cluster" includes:

[0144] S601, based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time.

[0145] The second duration is a reference value obtained by statistically analyzing the estimated deadline for effective clusters.

[0146] As an alternative implementation, the median method can be used to select the median of the first duration among battery clusters with a confidence level higher than a preset threshold as the second duration, in order to reduce the impact of extreme values.

[0147] As another optional implementation, the credibility of each target battery cluster can be used as a weighting factor to weight the first duration of each target battery cluster, and the second duration required for the battery stack to reach the charge / discharge cutoff time can be obtained based on the weighted processing result. Among them, the battery cluster with higher credibility has a larger proportion in the weighted calculation, and the first duration of the battery cluster contributes more to the second duration.

[0148] Optionally, the weighted result obtained by weighting the first duration of each target battery cluster based on the credibility of each target battery cluster can be used as the second duration. For example, the second duration... Among them, under charging conditions Under discharge conditions .

[0149] Optionally, such as Figure 7 As shown, the aforementioned "determining the second duration required for the battery stack to reach the charge / discharge cutoff time based on the confidence level of at least one battery cluster and the first duration" includes:

[0150] S701, calculate the sum of the products of the reliability of the battery clusters in the battery stack and the first duration, and use it as the first sum value.

[0151] S702, calculate the sum of the confidence levels of the battery clusters in the battery stack, and use it as the second sum value.

[0152] S703, the ratio of the first sum to the second sum is used as the second duration.

[0153] For example, the first sum can be Among them, under charging conditions Under discharge conditions The second sum can be Furthermore, the second duration is shown in Equation 12:

[0154] (Equation 12)

[0155] S602, based on the second duration, and the first duration of the target battery cluster involved in charge-discharge control, the current cluster temperature, the current health state, and the current state of charge, determine the coordination parameters of the target battery cluster.

[0156] The coordination parameter is used to quantify the extent to which each target battery cluster needs to reach the cutoff boundary earlier or later at the end of charging and discharging.

[0157] In this embodiment of the application, the first duration and the second duration of each target battery cluster are compared to obtain the progress deviation of each target battery cluster relative to the battery stack as a whole. Then, the progress deviation of the target battery cluster relative to the battery stack as a whole is corrected by combining the current cluster temperature, current health status and current state of charge, and finally the coordination parameters of the target battery cluster are determined.

[0158] As an optional implementation, the ratio or difference between the first duration and the second duration is first determined as an initial deviation factor. Then, the temperature correction coefficient, health status correction coefficient, and state of charge offset are determined according to the current cluster temperature, health status, and state of charge of each target battery cluster. The basic deviation factor and the above correction amount are converted into coordination parameters through a preset mapping relationship.

[0159] As another optional implementation, the first duration, second duration, current cluster temperature, health status, and state of charge of each target battery cluster are combined into a feature vector, which is then input into a pre-trained regression model, and the regression model outputs coordination parameters.

[0160] S603 adjusts the virtual state of charge of the target battery cluster according to the coordination parameters of the target battery cluster.

[0161] In this embodiment of the application, the adjustment direction and adjustment amount of the virtual state of charge of each target battery cluster are determined based on the coordination parameters of each target battery cluster, and the corresponding virtual state of charge is updated according to the adjustment direction and adjustment amount.

[0162] Optionally, the current virtual state of charge of the target battery cluster is updated according to the coordination parameters of the target battery cluster and the change in state of charge of the battery stack to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0163] For example, updating the current virtual state of charge of the target battery cluster can be done as shown in Equation 13:

[0164] (Equation 13)

[0165] in, This represents the current virtual state of charge. For the new virtual state of charge This is the change in state of charge. For the coordination coefficient, under charging conditions Charging coordination coefficient Under discharge conditions Discharge Coordination Coefficient .

[0166] In the above-mentioned embodiments, coordination parameters are determined by combining the temperature, health status and state of charge differences of each target battery cluster with the second duration, thereby dynamically adjusting the virtual state of charge. This allows each battery cluster to adjust its charging and discharging depth according to its own state at the end of the charging and discharging process, improving the charging and discharging consistency among the battery clusters within the battery stack, avoiding premature triggering of the entire stack protection by a single lagging battery cluster, and improving the overall energy utilization efficiency of the battery stack.

[0167] In one embodiment, one implementation of S602 described above is provided, such as... Figure 8 As shown, the aforementioned "determining the coordination parameters of the target battery cluster based on the second duration, the first duration of the target battery cluster involved in charge-discharge control, the current cluster temperature, the current health state, and the current state of charge" includes:

[0168] S801 determines the attenuation cost parameters of the target battery cluster based on the state information of the target battery cluster.

[0169] Among them, the degradation cost parameter of the target battery cluster is used to characterize the lifetime cost of the target battery cluster continuing to bear the end pressure when it continues to charge and discharge in the current state.

[0170] In this embodiment, the current cluster temperature, current health status, and current state of charge can be substituted into a pre-set functional relationship or mapping table to obtain the attenuation cost terms corresponding to each factor. Then, the attenuation cost terms are calculated using a preset calculation rule to obtain the attenuation cost parameters.

[0171] Optionally, the current cluster temperature is substituted into the temperature-aging acceleration factor curve to obtain the temperature cost term; the current state of charge is substituted into the state of charge-aging influence function to obtain the state of charge cost term; and the health state cost term corresponding to the current health state is determined based on a preset mapping relationship.

[0172] S802, based on the attenuation cost parameter of the target battery cluster and the first duration and the second duration, obtain the coordination parameter of the target battery cluster.

[0173] As an optional implementation, the attenuation cost parameter, the first duration, and the second duration can be substituted into a preset coordination parameter function to obtain the coordination parameters of the target battery cluster.

[0174] As another alternative implementation, the attenuation cost parameter can be combined with the first duration to obtain the equivalent remaining duration of the target battery cluster under the influence of aging, and then the equivalent remaining duration can be compared with the second duration to obtain the coordination parameter.

[0175] In the above-mentioned application embodiments, by combining the attenuation cost parameter, the first duration and the second duration, the determination of the coordination parameter reflects both the aging state of the target battery cluster and the time comparison between the target battery cluster and the battery stack as a whole reaching the cutoff boundary, thereby improving the rationality of the coordinated control at the end of charging and discharging.

[0176] In one embodiment, one implementation of the above S802 is provided, such as... Figure 9 As shown, the aforementioned "obtaining the coordination parameters of the target battery cluster based on the attenuation cost parameters of the target battery cluster, the first duration, and the second duration" includes:

[0177] S901, determine the initial duration difference between the first duration and the second duration.

[0178] In this embodiment of the application, under charging conditions, the initial duration difference between the first duration and the second duration is: Under discharge conditions, the initial duration difference between the first and second durations. .

[0179] S902, normalizes the initial duration difference according to the preset bandwidth to obtain the target duration difference.

[0180] In this embodiment of the application, under charging conditions, the target duration difference is... Under discharge conditions, the target duration difference is: .in, This is the normalized bandwidth based on the preset deadline time difference.

[0181] S903, based on the first weight corresponding to the target duration difference and the second weight corresponding to the attenuation cost parameter, perform a weighted summation on the target duration difference and the attenuation cost parameter to obtain the weighted summation result.

[0182] S904, based on the weighted summation result, obtains the coordination parameters of the target battery cluster.

[0183] In this embodiment, the first weight can be represented as a, and the second weight can be represented as b. Under charging conditions, the coordination parameters are shown in Equation 14, and under discharging conditions, the coordination parameters are shown in Equation 15.

[0184] (Equation 14)

[0185] (Equation 15)

[0186] Optionally, battery clusters that are expected to reach the cutoff boundary earlier will have a reduced coordination coefficient, thereby slowing down the rate of change of their control SOC during subsequent control SOC updates. To prevent abnormal fluctuations or over-adjustment of the coordination coefficient, threshold judgment, amplitude limiting, smoothing, or hysteresis processing can be applied to the coordination coefficient.

[0187] In this embodiment of the application, the coordination parameter is calculated by combining the attenuation cost parameter, the first duration and the second duration, so that the determination of the coordination parameter incorporates the battery aging state and the time comparison relationship with the battery stack as a whole.

[0188] In one embodiment, one implementation of the above S801 is provided, such as... Figure 10 As shown, the above-mentioned "determining the attenuation cost parameters of the target battery cluster based on the state information of the target battery cluster" includes:

[0189] S1001, based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster.

[0190] In the embodiments of this application, the attenuation cost term may include a temperature cost term, a state of charge cost term, and a health state cost term.

[0191] Optionally, the health status cost term is shown in Equation 16, the temperature cost term is shown in Equation 17, the state of charge cost term under charging conditions is shown in Equation 18, and the state of charge cost term under discharging conditions is shown in Equation 19.

[0192] (Equation 16)

[0193] (Equation 17)

[0194] (Equation 18)

[0195] (Equation 19)

[0196] in, For the first Current health status of each battery cluster For reference temperature; For temperature-normalized bandwidth; This is the starting point for high SOC aging sensitivity, i.e., the initial value of the SOC aging sensitivity zone under charging conditions; This is the starting point for low SOC aging sensitivity, i.e., the initial value of the SOC aging sensitivity zone under discharge conditions.

[0197] S1002, based on the multiple attenuation sub-components of the target battery cluster, obtain the attenuation cost parameters of the target battery cluster.

[0198] In this embodiment of the application, the attenuation cost parameter can be expressed as: .in, This is a cost term for health status; it increases as SOH decreases. This is a temperature-related cost term, which increases with increasing temperature. This is the state-of-charge cost term, which increases as the state of charge (SOC) approaches the aging-sensitive region at the end. Under charging conditions, for Under discharge conditions, for ; , , Weighted by aging cost.

[0199] In the above-mentioned application embodiments, by determining the attenuation sub-components corresponding to each state parameter separately and then fusing them into a comprehensive attenuation cost parameter, the independent contribution of each aging influencing factor to battery attenuation can be refined, making the attenuation cost parameter more accurately reflect the comprehensive aging degree of the target battery cluster in the current state.

[0200] In one embodiment, a complete charging and discharging control method for an energy storage system is provided, including:

[0201] S1, under the condition of charging and discharging of the battery stack, collect the status information of at least one battery cluster in the battery stack.

[0202] S2, determine the current charging and discharging condition of the battery stack. If the current charging and discharging condition of the battery stack is a charging condition, and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold, determine that the battery cluster is at the charging end of the current charging and discharging condition. If the current charging and discharging condition of the battery stack is a discharging condition, and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharging threshold, determine that the battery cluster is at the discharging end of the current charging and discharging condition.

[0203] S3, when it is identified that at least one battery cluster is at the end of the current charge / discharge condition, the predicted cluster voltage of at least one battery cluster at the current moment is predicted based on the battery model.

[0204] S4. Based on the difference between the predicted cluster voltage and the current cluster voltage of at least one battery cluster at the current moment, the confidence level of at least one battery cluster is calculated.

[0205] S5, based on the credibility of at least one battery cluster and the state information of at least one battery cluster, determine at least one target battery cluster participating in charge-discharge control from the battery stack.

[0206] S6, determine the current equivalent available capacity of the target battery cluster based on the current health status of the target battery cluster.

[0207] S7. Determine the current remaining charge / discharge capacity of the target battery cluster based on its current equivalent available capacity and current state of charge.

[0208] S8, determine the first duration of the target battery cluster based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0209] S9, based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time.

[0210] S10, based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster.

[0211] S11. Based on the multiple attenuation sub-components of the target battery cluster, the attenuation cost parameters of the target battery cluster are obtained.

[0212] S12, based on the attenuation cost parameter of the target battery cluster, the first duration, and the second duration, obtain the coordination parameters of the target battery cluster.

[0213] S13. Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, update the current virtual state of charge of the target battery cluster to obtain a new virtual state of charge, and use the new virtual state of charge as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0214] In the aforementioned energy storage system's charge / discharge control method, during the charging and discharging of the battery stack, the state information of at least one battery cluster in the stack is collected; the current charging / discharging condition of the battery stack is determined, and when at least one battery cluster is identified as being at the end of the current charging / discharging condition, the first time it takes for the at least one battery cluster to reach the charge / discharge cutoff boundary from its current state of charge is predicted based on the state information of the at least one battery cluster; the virtual state of charge of the at least one battery cluster is adjusted based on the first time and state information corresponding to the at least one battery cluster; the virtual state of charge coordinates the charge / discharge depth of the at least one battery cluster at the end of the charging / discharging process. By predicting the first time for each battery cluster to reach the charge / discharge cutoff boundary and dynamically adjusting the virtual state of charge of each battery cluster based on each first time, the coordinated balance of the charge / discharge depth of each battery cluster at the end of the charging / discharging process is achieved, preventing the charge / discharge depth of the battery stack from being compressed and avoiding the problem of some battery clusters entering the cutoff protection too early, which would lead to a decrease in the usable capacity of the entire stack. This improves the overall energy utilization rate of the battery stack and extends its service life.

[0215] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0216] Based on the same inventive concept, this application also provides an embodiment for implementing the energy storage system described above. The solution provided by this energy storage system is similar to the solution described in the above method; therefore, the specific limitations of one or more energy storage system embodiments provided below can be found in the limitations of the charging and discharging control method of the energy storage system described above, and will not be repeated here.

[0217] In one embodiment, such as Figure 11As shown, an energy storage system is provided, including: a data acquisition module 10, a determination module 11, and an adjustment module 12, wherein:

[0218] The acquisition module 10 is used to acquire the status information of at least one battery cluster in the battery stack when the battery stack is being charged and discharged.

[0219] The determination module 11 is used to determine the current charging and discharging condition of the battery stack, and when it is identified that at least one battery cluster is at the end of the current charging and discharging condition, it predicts the first time that at least one battery cluster will take from the current state of charge to reach the charging and discharging cutoff boundary based on the state information of at least one battery cluster.

[0220] The adjustment module 12 is used to adjust the virtual state of charge of at least one battery cluster according to the first duration and state information corresponding to at least one battery cluster; the virtual state of charge coordinates the charge and discharge depth of at least one battery cluster at the end of the charge and discharge process.

[0221] In one embodiment, the determining module 11 includes: a first determining unit, a second determining unit, and a third determining unit, wherein:

[0222] The first determining unit is used to determine the confidence level of at least one battery cluster based on the battery model and the current cluster voltage of at least one battery cluster.

[0223] The second determining unit is used to determine at least one target battery cluster participating in charge-discharge control from the battery stack based on the credibility of at least one battery cluster and the state information of at least one battery cluster.

[0224] The third determining unit is used to determine the first duration of the target battery cluster based on the charging and discharging current, current state of charge, and health status of the target battery cluster involved in the charging and discharging control.

[0225] In one embodiment, the first determining unit is specifically used to predict the predicted cluster voltage of at least one battery cluster at the current moment based on the battery model; and to calculate the confidence level of at least one battery cluster based on the difference between the predicted cluster voltage of at least one battery cluster at the current moment and the current cluster voltage.

[0226] In one embodiment, the third determining unit is specifically configured to determine the current equivalent available capacity of the target battery cluster based on the current health status of the target battery cluster; determine the current remaining charge / discharge capacity of the target battery cluster based on the current equivalent available capacity and the current state of charge of the target battery cluster; and determine the first duration of the target battery cluster based on the current remaining charge / discharge capacity and the charge / discharge current of the target battery cluster.

[0227] In one embodiment, the adjustment module 12 includes: a fourth determining unit, a fifth determining unit, and an adjustment unit, wherein:

[0228] The fourth determining unit is used to determine the second duration required for the battery stack to reach the charge / discharge cutoff time based on the confidence level of at least one battery cluster and the first duration.

[0229] The fifth determining unit is used to determine the coordination parameters of the target battery cluster based on the second duration, the first duration of the target battery cluster involved in charge-discharge control, the current cluster temperature, the current health state, and the current state of charge.

[0230] The adjustment unit is used to adjust the virtual state of charge of the target battery cluster according to the coordination parameters of the target battery cluster.

[0231] In one embodiment, the adjustment unit is specifically used to update the current virtual state of charge of the target battery cluster according to the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, to obtain a new virtual state of charge, and to use the new virtual state of charge as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0232] In one embodiment, the fifth determining unit is specifically used to determine the attenuation cost parameter of the target battery cluster based on the state information of the target battery cluster; and to obtain the coordination parameter of the target battery cluster based on the attenuation cost parameter of the target battery cluster, the first duration, and the second duration.

[0233] In one embodiment, the fifth determining unit is specifically used to determine multiple attenuation sub-components of the target battery cluster according to multiple state parameters in the state information of the target battery cluster; and to obtain the attenuation cost parameter of the target battery cluster according to the multiple attenuation sub-components of the target battery cluster.

[0234] In one embodiment, the determining module 11 is further configured to determine that the battery cluster is at the charging end of the current charging and discharging condition when the current charging and discharging condition of the battery stack is a charging condition and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold; and to determine that the battery cluster is at the discharging end of the current charging and discharging condition when the current charging and discharging condition of the battery stack is a discharging condition and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharging threshold.

[0235] Each module in the aforementioned energy storage system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0236] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 12 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores charging and discharging control data for the energy storage system. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a charging and discharging control method for an energy storage system.

[0237] Those skilled in the art will understand that Figure 12 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0238] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0239] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0240] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0241] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0242] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0243] Based on the battery model and the current cluster voltage of at least one battery cluster, the confidence level of at least one battery cluster is obtained;

[0244] Based on the credibility of at least one battery cluster and the state information of at least one battery cluster, at least one target battery cluster participating in charge and discharge control is determined from the battery stack;

[0245] The first duration of the target battery cluster is determined based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

[0246] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0247] Based on the battery model, the predicted cluster voltage of at least one battery cluster at the current moment is predicted;

[0248] The confidence level of at least one battery cluster is calculated based on the difference between the predicted cluster voltage and the current cluster voltage at the current moment.

[0249] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0250] Determine the current equivalent available capacity of the target battery cluster based on its current health status;

[0251] Determine the current remaining charge / discharge capacity of the target battery cluster based on its current equivalent available capacity and current state of charge.

[0252] The first duration of the target battery cluster is determined based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0253] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0254] Based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time;

[0255] Based on the second duration, and the first duration of the target battery cluster involved in charge and discharge control, the current cluster temperature, the current health status, and the current state of charge, the coordination parameters of the target battery cluster are determined.

[0256] The virtual state of charge of the target battery cluster is adjusted based on the coordination parameters of the target battery cluster.

[0257] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0258] Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, the current virtual state of charge of the target battery cluster is updated to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0259] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0260] Based on the state information of the target battery cluster, determine the degradation cost parameters of the target battery cluster;

[0261] Based on the attenuation cost parameters of the target battery cluster and the first and second durations, the coordination parameters of the target battery cluster are obtained.

[0262] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0263] Based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster;

[0264] The attenuation cost parameters of the target battery cluster are obtained based on multiple attenuation sub-components of the target battery cluster.

[0265] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0266] When the current charge / discharge condition of the battery stack is the charging condition, and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold, the battery cluster is determined to be at the end of the charging phase of the current charge / discharge condition.

[0267] When the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharge threshold, the battery cluster is determined to be at the end of the discharge of the current charge / discharge condition.

[0268] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0269] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0270] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0271] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0272] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0273] Based on the battery model and the current cluster voltage of at least one battery cluster, the confidence level of at least one battery cluster is obtained;

[0274] Based on the credibility of at least one battery cluster and the state information of at least one battery cluster, at least one target battery cluster participating in charge and discharge control is determined from the battery stack;

[0275] The first duration of the target battery cluster is determined based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

[0276] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0277] Based on the battery model, the predicted cluster voltage of at least one battery cluster at the current moment is predicted;

[0278] The confidence level of at least one battery cluster is calculated based on the difference between the predicted cluster voltage and the current cluster voltage at the current moment.

[0279] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0280] Determine the current equivalent available capacity of the target battery cluster based on its current health status;

[0281] Determine the current remaining charge / discharge capacity of the target battery cluster based on its current equivalent available capacity and current state of charge.

[0282] The first duration of the target battery cluster is determined based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0283] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0284] Based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time;

[0285] Based on the second duration, and the first duration of the target battery cluster involved in charge and discharge control, the current cluster temperature, the current health status, and the current state of charge, the coordination parameters of the target battery cluster are determined.

[0286] The virtual state of charge of the target battery cluster is adjusted based on the coordination parameters of the target battery cluster.

[0287] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0288] Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, the current virtual state of charge of the target battery cluster is updated to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0289] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0290] Based on the state information of the target battery cluster, determine the degradation cost parameters of the target battery cluster;

[0291] Based on the attenuation cost parameters of the target battery cluster and the first and second durations, the coordination parameters of the target battery cluster are obtained.

[0292] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0293] Based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster;

[0294] The attenuation cost parameters of the target battery cluster are obtained based on multiple attenuation sub-components of the target battery cluster.

[0295] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0296] When the current charge / discharge condition of the battery stack is the charging condition, and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold, the battery cluster is determined to be at the end of the charging phase of the current charge / discharge condition.

[0297] When the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharge threshold, the battery cluster is determined to be at the end of the discharge of the current charge / discharge condition.

[0298] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0299] During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected;

[0300] When the current charge and discharge condition of the battery stack is determined and at least one battery cluster is identified as being at the end of the charge and discharge condition, the first time duration from the current state of charge of the at least one battery cluster to the charge and discharge cutoff boundary is predicted based on the state information of the at least one battery cluster.

[0301] Based on the first duration and state information corresponding to at least one battery cluster, the virtual state of charge of at least one battery cluster is adjusted; the virtual state of charge coordinates the depth of charge and discharge of at least one battery cluster at the end of the charge and discharge cycle.

[0302] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0303] Based on the battery model and the current cluster voltage of at least one battery cluster, the confidence level of at least one battery cluster is obtained;

[0304] Based on the credibility of at least one battery cluster and the state information of at least one battery cluster, at least one target battery cluster participating in charge and discharge control is determined from the battery stack;

[0305] The first duration of the target battery cluster is determined based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

[0306] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0307] Based on the battery model, the predicted cluster voltage of at least one battery cluster at the current moment is predicted;

[0308] The confidence level of at least one battery cluster is calculated based on the difference between the predicted cluster voltage and the current cluster voltage at the current moment.

[0309] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0310] Determine the current equivalent available capacity of the target battery cluster based on its current health status;

[0311] Determine the current remaining charge / discharge capacity of the target battery cluster based on its current equivalent available capacity and current state of charge.

[0312] The first duration of the target battery cluster is determined based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

[0313] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0314] Based on the confidence level of at least one battery cluster and the first duration, determine the second duration required for the battery stack to reach the charge / discharge cutoff time;

[0315] Based on the second duration, and the first duration of the target battery cluster involved in charge and discharge control, the current cluster temperature, the current health status, and the current state of charge, the coordination parameters of the target battery cluster are determined.

[0316] The virtual state of charge of the target battery cluster is adjusted based on the coordination parameters of the target battery cluster.

[0317] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0318] Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, the current virtual state of charge of the target battery cluster is updated to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

[0319] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0320] Based on the state information of the target battery cluster, determine the degradation cost parameters of the target battery cluster;

[0321] Based on the attenuation cost parameters of the target battery cluster and the first and second durations, the coordination parameters of the target battery cluster are obtained.

[0322] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0323] Based on multiple state parameters in the state information of the target battery cluster, determine the corresponding multiple attenuation sub-components of the target battery cluster;

[0324] The attenuation cost parameters of the target battery cluster are obtained based on multiple attenuation sub-components of the target battery cluster.

[0325] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0326] When the current charge / discharge condition of the battery stack is the charging condition, and the current state of charge of at least one battery cluster is greater than or equal to the state of charge charging threshold, the battery cluster is determined to be at the end of the charging phase of the current charge / discharge condition.

[0327] When the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge of at least one battery cluster is less than or equal to the state of charge discharge threshold, the battery cluster is determined to be at the end of the discharge of the current charge / discharge condition.

[0328] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0329] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0330] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A charging and discharging control method for an energy storage system, characterized in that, The method includes: During the charging and discharging of the battery stack, the status information of at least one battery cluster in the battery stack is collected; When the current charging and discharging condition of the battery stack is determined, and the at least one battery cluster is identified as being at the end of the charging and discharging process of the current charging and discharging condition, the first time duration from the current state of charge of the at least one battery cluster to the charging and discharging cutoff boundary is predicted based on the state information of the at least one battery cluster. Based on the first duration and state information corresponding to the at least one battery cluster, the virtual state of charge of the at least one battery cluster is adjusted; the virtual state of charge coordinates the charge and discharge depth of the at least one battery cluster at the end of the charge and discharge process.

2. The charging and discharging control method for an energy storage system according to claim 1, characterized in that, The status information includes the current cluster voltage, current charge / discharge current, current state of charge, and current health state of the at least one battery cluster; the step of predicting the first time interval for the at least one battery cluster to reach the charge / discharge cutoff boundary from the current state of charge, based on the status information of the at least one battery cluster, includes: The confidence level of the at least one battery cluster is obtained based on the battery model and the current cluster voltage of the at least one battery cluster. Based on the reliability of the at least one battery cluster and the state information of the at least one battery cluster, at least one target battery cluster participating in charge and discharge control is determined from the battery stack; The first duration of the target battery cluster is determined based on the charge / discharge current, current state of charge, and health status of the target battery cluster involved in charge / discharge control.

3. The charging and discharging control method for an energy storage system according to claim 2, characterized in that, The step of obtaining the confidence level of the at least one battery cluster based on the battery model and the current cluster voltage of the at least one battery cluster includes: Based on the battery model, the predicted cluster voltage of the at least one battery cluster at the current moment is predicted; The confidence level of the at least one battery cluster is calculated based on the difference between the predicted cluster voltage and the current cluster voltage at the current moment.

4. The charging and discharging control method for an energy storage system according to claim 2, characterized in that, The step of determining the first duration of the target battery cluster based on the charge / discharge current, current state of charge, and health state of the target battery cluster involved in charge / discharge control includes: Based on the current health status of the target battery cluster, determine the current equivalent available capacity of the target battery cluster; The current remaining charge / discharge capacity of the target battery cluster is determined based on its current equivalent available capacity and current state of charge. The first duration of the target battery cluster is determined based on the current remaining charge / discharge capacity and charge / discharge current of the target battery cluster.

5. The charging and discharging control method for an energy storage system according to claim 2, characterized in that, The status information also includes the current cluster temperature of the at least one battery cluster; adjusting the virtual state of charge of the at least one battery cluster according to the first duration and status information corresponding to the at least one battery cluster includes: Based on the confidence level of the at least one battery cluster and the first duration, a second duration required for the battery stack to reach the charge / discharge cutoff time is determined; Based on the second duration, and the first duration of the target battery cluster involved in charge and discharge control, the current cluster temperature, the current health status, and the current state of charge, the coordination parameters of the target battery cluster are determined; The virtual state of charge of the target battery cluster is adjusted according to the coordination parameters of the target battery cluster.

6. The charging and discharging control method for an energy storage system according to claim 5, characterized in that, The step of adjusting the virtual state of charge of the target battery cluster according to the coordination parameters of the target battery cluster includes: Based on the coordination parameters of the target battery cluster and the change in state of charge of the battery stack, the current virtual state of charge of the target battery cluster is updated to obtain a new virtual state of charge, and the new virtual state of charge is used as the virtual state of charge of the target battery cluster; the change in state of charge is the change in state of charge of the battery stack from the beginning of the current charge-discharge cycle to the current time.

7. The charging and discharging control method for an energy storage system according to claim 5, characterized in that, The determination of coordination parameters for the target battery cluster based on the second duration, the first duration of the target battery cluster involved in charge / discharge control, the current cluster temperature, the current health state, and the current state of charge includes: Based on the state information of the target battery cluster, determine the attenuation cost parameter of the target battery cluster; Based on the attenuation cost parameter of the target battery cluster, the first duration, and the second duration, the coordination parameters of the target battery cluster are obtained.

8. The charging and discharging control method for an energy storage system according to claim 7, characterized in that, The step of determining the attenuation cost parameter of the target battery cluster based on the state information of the target battery cluster includes: Based on multiple state parameters in the state information of the target battery cluster, the corresponding multiple attenuation sub-components of the target battery cluster are determined respectively; The attenuation cost parameter of the target battery cluster is obtained based on multiple attenuation sub-components of the target battery cluster.

9. The charging and discharging control method for an energy storage system according to any one of claims 1-8, characterized in that, After determining the current charge / discharge condition of the battery stack, the method further includes: When the current charge / discharge condition of the battery stack is a charging condition, and the current state of charge of at least one of the battery clusters is greater than or equal to the state of charge charging threshold, the battery cluster is determined to be at the end of the charging process of the current charge / discharge condition. When the current charge / discharge condition of the battery stack is a discharge condition, and the current state of charge of at least one of the battery clusters is less than or equal to the state of charge discharge threshold, the battery cluster is determined to be at the end of the discharge of the current charge / discharge condition.

10. An energy storage system, characterized in that, The energy storage system performs the steps of the method as described in any one of claims 1 to 9, the energy storage system comprising: The acquisition module is used to acquire the status information of at least one battery cluster in the battery stack during charging and discharging. The determination module is used to determine the current charging and discharging condition of the battery stack, and when it is identified that at least one battery cluster is at the end of the charging and discharging of the current charging and discharging condition, it predicts the first time from the current state of charge of the at least one battery cluster to the charging and discharging cutoff boundary based on the state information of the at least one battery cluster. An adjustment module is used to adjust the virtual state of charge of the at least one battery cluster according to the first duration and state information corresponding to the at least one battery cluster; the virtual state of charge coordinates the charge and discharge depth of the at least one battery cluster at the end of the charge and discharge process.

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